am db3a6c44: Merge "CameraITS: Updates to test_crop_regions_raw" into lmp-sprout-dev
* commit 'db3a6c445106c6dc93cba0f2c170050498de9a41':
CameraITS: Updates to test_crop_regions_raw
diff --git a/apps/CameraITS/tests/scene1/test_crop_region_raw.py b/apps/CameraITS/tests/scene1/test_crop_region_raw.py
index 9fc52cb..189e987 100644
--- a/apps/CameraITS/tests/scene1/test_crop_region_raw.py
+++ b/apps/CameraITS/tests/scene1/test_crop_region_raw.py
@@ -20,25 +20,6 @@
import numpy
import os.path
-
-def check_crop_region(expected, reported, active, err_threshold):
- """Check if the reported region is within the tolerance.
-
- Args:
- expected: expected crop region
- reported: reported crop region
- active: active resolution
- err_threshold: error threshold for the active resolution
- """
-
- ex = (active["right"] - active["left"]) * err_threshold
- ey = (active["bottom"] - active["top"]) * err_threshold
-
- assert ((abs(expected["left"] - reported["left"]) <= ex) and
- (abs(expected["right"] - reported["right"]) <= ex) and
- (abs(expected["top"] - reported["top"]) <= ey) and
- (abs(expected["bottom"] - reported["bottom"]) <= ey))
-
def main():
"""Test that raw streams are not croppable.
"""
@@ -53,6 +34,7 @@
its.caps.raw16(props) and
its.caps.per_frame_control(props))
+ # Calculate the active sensor region for a full (non-cropped) image.
a = props['android.sensor.info.activeArraySize']
ax, ay = a["left"], a["top"]
aw, ah = a["right"] - a["left"], a["bottom"] - a["top"]
@@ -65,6 +47,19 @@
"bottom": ah
}
+ # Calculate a center crop region.
+ zoom = min(3.0, its.objects.get_max_digital_zoom(props))
+ assert(zoom >= 1)
+ cropw = aw / zoom
+ croph = ah / zoom
+
+ crop_region = {
+ "left": aw / 2 - cropw / 2,
+ "top": ah / 2 - croph / 2,
+ "right": aw / 2 + cropw / 2,
+ "bottom": ah / 2 + croph / 2
+ }
+
# Capture without a crop region.
# Use a manual request with a linear tonemap so that the YUV and RAW
# should look the same (once converted by the its.image module).
@@ -72,59 +67,57 @@
req = its.objects.manual_capture_request(s,e, True)
cap1_raw, cap1_yuv = cam.do_capture(req, cam.CAP_RAW_YUV)
- # Calculate a center crop region.
- zoom = min(3.0, its.objects.get_max_digital_zoom(props))
- assert(zoom >= 1)
- cropw = aw / zoom
- croph = ah / zoom
-
- req["android.scaler.cropRegion"] = {
- "left": aw / 2 - cropw / 2,
- "top": ah / 2 - croph / 2,
- "right": aw / 2 + cropw / 2,
- "bottom": ah / 2 + croph / 2
- }
-
- # when both YUV and RAW are requested, the crop region that's
- # applied to YUV should be reported.
- crop_region = req["android.scaler.cropRegion"]
- if crop_region == full_region:
- crop_region_err_thresh = 0.0
- else:
- crop_region_err_thresh = CROP_REGION_ERROR_THRESHOLD
-
+ # Capture with a crop region.
+ req["android.scaler.cropRegion"] = crop_region
cap2_raw, cap2_yuv = cam.do_capture(req, cam.CAP_RAW_YUV)
+ # Check the metadata related to crop regions.
+ # When both YUV and RAW are requested, the crop region that's
+ # applied to YUV should be reported.
+ # Note that the crop region returned by the cropped captures doesn't
+ # need to perfectly match the one that was requested.
imgs = {}
- for s, cap, cr, err_delta in [("yuv_full", cap1_yuv, full_region, 0),
- ("raw_full", cap1_raw, full_region, 0),
- ("yuv_crop", cap2_yuv, crop_region, crop_region_err_thresh),
- ("raw_crop", cap2_raw, crop_region, crop_region_err_thresh)]:
+ for s, cap, cr_expected, err_delta in [
+ ("yuv_full",cap1_yuv,full_region,0),
+ ("raw_full",cap1_raw,full_region,0),
+ ("yuv_crop",cap2_yuv,crop_region,CROP_REGION_ERROR_THRESHOLD),
+ ("raw_crop",cap2_raw,crop_region,CROP_REGION_ERROR_THRESHOLD)]:
+
+ # Convert the capture to RGB and dump to a file.
img = its.image.convert_capture_to_rgb_image(cap, props=props)
its.image.write_image(img, "%s_%s.jpg" % (NAME, s))
- r = cap["metadata"]["android.scaler.cropRegion"]
- x, y = r["left"], r["top"]
- w, h = r["right"] - r["left"], r["bottom"] - r["top"]
imgs[s] = img
- print "Crop on %s: (%d,%d %dx%d)" % (s, x, y, w, h)
- check_crop_region(cr, r, a, err_delta)
+
+ # Get the crop region that is reported in the capture result.
+ cr_reported = cap["metadata"]["android.scaler.cropRegion"]
+ x, y = cr_reported["left"], cr_reported["top"]
+ w = cr_reported["right"] - cr_reported["left"]
+ h = cr_reported["bottom"] - cr_reported["top"]
+ print "Crop reported on %s: (%d,%d %dx%d)" % (s, x, y, w, h)
+
+ # Test that the reported crop region is the same as the expected
+ # one, for a non-cropped capture, and is close to the expected one,
+ # for a cropped capture.
+ ex = aw * err_delta
+ ey = ah * err_delta
+ assert ((abs(cr_expected["left"] - cr_reported["left"]) <= ex) and
+ (abs(cr_expected["right"] - cr_reported["right"]) <= ex) and
+ (abs(cr_expected["top"] - cr_reported["top"]) <= ey) and
+ (abs(cr_expected["bottom"] - cr_reported["bottom"]) <= ey))
# Also check the image content; 3 of the 4 shots should match.
# Note that all the shots are RGB below; the variable names correspond
# to what was captured.
- # Average the images down 4x4 -> 1 prior to comparison to smooth out
- # noise.
- # Shrink the YUV images an additional 2x2 -> 1 to account for the size
- # reduction that the raw images went through in the RGB conversion.
+
+ # Shrink the YUV images 2x2 -> 1 to account for the size reduction that
+ # the raw images went through in the RGB conversion.
imgs2 = {}
for s,img in imgs.iteritems():
h,w,ch = img.shape
- m = 4
if s in ["yuv_full", "yuv_crop"]:
- m = 8
- img = img.reshape(h/m,m,w/m,m,3).mean(3).mean(1).reshape(h/m,w/m,3)
+ img = img.reshape(h/2,2,w/2,2,3).mean(3).mean(1)
+ img = img.reshape(h/2,w/2,3)
imgs2[s] = img
- print s, img.shape
# Strip any border pixels from the raw shots (since the raw images may
# be larger than the YUV images). Assume a symmetric padded border.
@@ -139,7 +132,10 @@
for s,img in imgs2.iteritems():
its.image.write_image(img, "%s_comp_%s.jpg" % (NAME, s))
- # Compute image diffs.
+ # Compute diffs between images of the same type.
+ # The raw_crop and raw_full shots should be identical (since the crop
+ # doesn't apply to raw images), and the yuv_crop and yuv_full shots
+ # should be different.
diff_yuv = numpy.fabs((imgs2["yuv_full"] - imgs2["yuv_crop"])).mean()
diff_raw = numpy.fabs((imgs2["raw_full"] - imgs2["raw_crop"])).mean()
print "YUV diff (crop vs. non-crop):", diff_yuv